# Settlement Timing String Normalisation and Missing-Value Fill

> Settlement Timing String Normalisation and Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Normalises string fields and fills missing values in settlement timing records (settlement_minutes, payment_count) for up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-18-037?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/settlement-timing-string-normalisation-and-missing-value-fill-d524e338
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_f1fUZmwtdI1MRHtP3e2AP

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability settlement-timing-string-normalisation-and-missing-value-fill-d524e338 -d '<json body>'
```

Example prompt: Clean up my settlement timing data — I have 4 rows with instrument groups 'group-a' and 'group-b', some missing settlement_minutes values, and I want to fill those gaps using median imputation. Can you normalise the strings and fill the missing values?

## When to prefer this

Choose this endpoint when you have raw settlement timing records with messy string fields or missing numeric values (settlement_minutes or payment_count) and need a quick, low-cost ($0.01 USDC) local analytical clean-up without live lookups, external data enrichment, or predictive modelling. It is ideal for pre-processing up to 200 rows before downstream reporting or analysis.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required row fields (row_id, instrument_group, date, settlement_minutes, payment_count) — validation error
- Invalid fill method value outside enum (zero, mean, median) — schema error
- Invalid field value outside enum (settlement_minutes, payment_count) — schema error
- Date not matching YYYY-MM-DD pattern — validation failure
- Payment failure or insufficient USDC balance — transaction rejected

## How this service works

Settlement timing — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied settlement timing records (settlement_minutes, payment_count). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Two analytical reports covering the submitted settlement timing rows: one for string normalisation results and one for explicit missing-value fill outcomes, applied to the chosen field (settlement_minutes or payment_count) using the selected method (zero, mean, or median).

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "instrument_group",
     "date",
     "settlement_minutes",
     "payment_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "payment_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "instrument_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "settlement_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "payment_count": 1,
     "instrument_group": "group-a",
     "settlement_minutes": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "payment_count": 2,
     "instrument_group": "group-b",
     "settlement_minutes": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "payment_count": 3,
     "instrument_group": "group-a",
     "settlement_minutes": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "payment_count": 4,
     "instrument_group": "group-b",
     "settlement_minutes": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "settlement_minutes",
    "payment_count"
   ],
   "type": "string",
   "default": "settlement_minutes"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/settlement-timing-string-normalisation-and-missing-value-fill-d524e338/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)